Competing ParA suctures space bacterial plasmids equally over the nucleoid

Low copy number plasmids in bacteria require segregation for stable inheritance through cell division. This is often achieved by a parABC locus, comprising an ATPase ParA, DNA-binding protein ParB and a parC region, encoding ParB-binding sites. These minimal components space plasmids equally over the nucleoid, yet the underlying mechanism is not understood. Here we investigate a model where ParA-ATP can dynamically associate to the nucleoid and is hydrolyzed by plasmid-associated ParB, thereby creating nucleoid-bound, self-organizing ParA concentration gradients. We show mathematically that differences between competing ParA concentrations on either side of a plasmid can specify regular plasmid positioning. Such positioning can be achieved regardless of the exact mechanism of plasmid movement, including plasmid diffusion with ParA-mediated immobilization or directed plasmid motion induced by ParB/parC-stimulated ParA structure disassembly. However, we find experimentally that parABC from Escherichia coli plasmid pB171 increases plasmid mobility, inconsistent with diffusion/immobilization. Instead our observations favor directed plasmid motion. Our model predicts less oscillatory ParA dynamics than previously believed, a prediction we verify experimentally. We also show that ParA localization and plasmid positioning depend on the underlying nucleoid morphology, indicating that the chromosomal architecture constrains ParA structure formation. Our directed motion model unifies previously contradictory models for plasmid segregation and provides a robust mechanistic basis for self-organized plasmid spacing that may be widely applicable

Weight and see: Line bisection in neglect reliably measures the allocation of attention, but not the perception of length

Line bisection has long been a routine test for unilateral neglect, along with a range of tests requiring cancellation, copying or drawing. However, several studies have reported that line bisection, as classically administered, correlates relatively poorly with the other tests of neglect, to the extent that some authors have questioned its status as a valid test of neglect. In this article, we re-examine this issue, employing a novel method for administering and analysing line bisection proposed by McIntosh et al. (2005). We report that the measure of attentional bias yielded by this new method (EWB) correlates significantly more highly with cancellation, copying and drawing measures than the classical line bisection error measure in a sample of 50 right-brain damaged patients. Furthermore when EWB was combined with a second measure that emerges from the new analysis (EWS), even higher correlations were obtained. A Principal Components Analysis found that EWB loaded highly on a major factor representing neglect asymmetry, while EWS loaded on a second factor which we propose may measure overall attentional investment. Finally, we found that tests of horizontal length and size perception were related poorly to other measures of neglect in our group. We conclude that this novel approach to interpreting line bisection behaviour provides a promising way forward for understanding the nature of neglect

Quantitative regulation of FLC via coordinated transcriptional initiation and elongation

The basis of quantitative regulation of gene expression is still poorly understood. In Arabidopsis thaliana, quantitative variation in expression of FLOWERING LOCUS C (FLC) influences the timing of flowering. In ambient temperatures, FLC expression is quantitatively modulated by a chromatin silencing mechanism involving alternative polyadenylation of antisense transcripts. Investigation of this mechanism unexpectedly showed that RNA polymerase II (Pol II) occupancy changes at FLC did not reflect RNA fold changes. Mathematical modeling of these transcriptional dynamics predicted a tight coordination of transcriptional initiation and elongation. This prediction was validated by detailed measurements of total and chromatin-bound FLC intronic RNA, a methodology appropriate for analyzing elongation rate changes in a range of organisms. Transcription initiation was found to vary ∼25-fold with elongation rate varying ∼8- to 12-fold. Premature sense transcript termination contributed very little to expression differences. This quantitative variation in transcription was coincident with variation in H3K36me3 and H3K4me2 over the FLC gene body. We propose different chromatin states coordinately influence transcriptional initiation and elongation rates and that this coordination is likely to be a general feature of quantitative gene regulation in a chromatin context

Reactions and propensities used in the diffusion/immobilization model.

<p>Reactions and propensities used in the diffusion/immobilization model.</p

Parameter values used in the diffusion/immobilization model.

<p>Parameter values used in the diffusion/immobilization model.</p

Reactions and propensities used in the directed motion models.

<p>Reactions and propensities used in the directed motion models.</p

Nucleoid morphology disruption causes aberrant plasmid focus positioning.

<p>(<b>A</b>) Fluorescence localization of ParB-GFP (green) and Hoechst DNA stain (blue) in <i>mukE</i>, <i>mukF</i>, <i>matP</i> mutants and wild-type cells treated with 50 µg/ml nalidixic acid (Nal). Scale bar: 1 µm; plasmid: pFS21 (mini-R1, <i>parC1⁺</i>, <i>parA⁺</i>, <i>parB::sfGFP</i>, <i>parC2⁺</i>). (<b>B</b>) Histograms of plasmid foci positions (n_p = 1,2) for mutants/treatments described in (<b>A</b>) relative to nucleoid size. According to Kolmogorov-Smirnov tests, all distributions are broader than WT (<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004009#pcbi-1004009-g001" target="_blank">Fig. 1C</a>) with p<10⁻² except Nal n_p = 1: p<0.05. (<b>C</b>) Manders overlap coefficients (error bars: standard error of the mean) of ParA-GFP comparing WT (n = 678) and Nal-treated cells (n = 862). Consistent with a decrease in the Pearson's correlation coefficient r_P (p<10⁻³⁸), ParA-GFP overlaps less with Hoechst in Nal-treated cells as compared to WT (p-values ranging from 10⁻⁵¹ to 10⁻¹⁴⁴). (<b>D</b>) Time-averaged plasmid position distributions for directed motion model with short polymers obtained as in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004009#pcbi-1004009-g002" target="_blank">Fig. 2C</a> from 124 independent simulations. Here, mobile DNA-bound ParA-ATP was now able to diffuse past a plasmid.</p

Parameter values used in the directed motion models.

<p>Parameter values used in the directed motion models.</p

Diffusion/immobilization model can move and maintain plasmids at equally spaced positions.

<p>(<b>A</b>) Schematic illustration of <i>par2</i> diffusion/immobilization model. The clock indicates the slow conversion of cytoplasmic ParA-ADP into cytoplasmic ParA-ATP that is competent to bind to the nucleoid. (<b>B</b>) Typical simulation kymograph of diffusion/immobilization model for growing cell, where plasmid (red) diffusion influenced by the local ParA-ATP (green) concentration leads to immobilization initially at mid cell. After plasmid duplication, the system dynamically self-organizes to reacquire equal plasmid spacing. (<b>C</b>) Time-averaged plasmid position distributions for diffusion/immobilization model with n_p = 1–2 on a simulated nucleoid growing from 1.5 µm to 3 µm in 40 min without plasmid duplication. Plasmid distributions were obtained by sampling positions every 5 s in 36 independent simulations.</p

ParA forms structures within the nucleoid region.

<p>(<b>A</b>) Fluorescence localization of ParA-GFP (green), Hoechst DNA stain (red) and overlay, at mid-height through cell, taken from deconvolved Z-stacks showing structures that are disrupted with 50 µg/ml nalidixic acid treatment (Nal) compared to WT. Scale bar: 1 µm; plasmid: pGE230 (mini-R1, <i>par^-</i>, <i>P_lac::parA::eGFP</i>). (<b>B</b>) Normalized fluorescence intensity profiles along the long cell axis for 9 in focus z heights (dz = 0.1 µm) resulting from deconvolved Z-stacks in representative WT and Nal-treated strains. (<b>C</b>) Manders overlap coefficients in WT cells (error bars: standard error of the mean, n = 678) showing the fraction of ParA-GFP fluorescence intensity that overlaps with Hoechst DNA stain when the latter is above a threshold T_Manders (ParA-GFP, green) and the reverse (Hoechst, red). ParA-GFP overlaps more with Hoechst DNA stain (p-values ranging from 10⁻¹² to 10⁻¹³², see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004009#s4" target="_blank">Materials and Methods</a>) than the reverse.</p